Best AI tools for< Learn Coding Basics >

Hugo is a personal GPT powered AI code mentor that helps you learn to code by providing real-time feedback and guidance. It is designed to be a comprehensive and interactive learning tool that can help you master the basics of coding and advance your skills.

Ordinary Prompts is a tool that helps users create better prompts for ChatGPT and other AI language models. It provides a library of pre-written prompts that can be used for a variety of tasks, such as generating creative content, getting help with coding, and writing emails. Ordinary Prompts also includes a number of features that make it easy to customize prompts and track your progress.

Fluffy Muffins is a super cool AI application that offers AI-powered assistants to help users learn fast, do better, and win big. The AI helpers, known as muffins, are designed to boost creativity, supercharge productivity, and add a sprinkle of fun to users' daily tasks. From accelerating learning to streamlining tasks and achieving ambitious goals, Fluffy Muffins aims to help users reach their full potential and celebrate their successes.

Adventure AI is an educational platform that offers kids the opportunity to work with cutting-edge AI technology to create games, art, music, and more. The platform provides a social gaming experience within Discord, where kids can engage in self-paced quests related to AI-assisted art, coding AI, and other paths of interest. Adventure AI aims to maximize intrinsic motivation in learning by making the AI tools engaging through games and real-world value creation. The platform also offers different pricing tiers with varying levels of access to AI tools and curriculum, including a community of kids collaborating on AI projects.

AICorr.com is a website offering free coding tutorials with a focus on artificial intelligence, data science, machine learning, and statistics. Users can learn and practice coding in Python and SQL, explore projects with real data, and access a wealth of information in an easy-to-understand format. The website aims to provide up-to-date and relevant information to a global audience, ensuring a seamless learning experience for all.

CodeKidz is an AI-driven learning platform designed for students and educators. It offers personalized learning experiences by leveraging artificial intelligence technology. The platform aims to enhance the learning process by providing tailored educational content and interactive activities. CodeKidz enables students to develop coding skills, problem-solving abilities, and critical thinking through engaging lessons and projects. Educators can track student progress, customize learning paths, and provide targeted support. With CodeKidz, users can explore the world of coding in a fun and interactive way, fostering creativity and innovation.

FavTutor AI Learning is an AI-powered tool designed to help users master programming skills through personalized learning experiences. The tool utilizes artificial intelligence algorithms to provide tailored lessons, practice exercises, and feedback to enhance the user's programming proficiency. With FavTutor AI Learning, users can improve their coding abilities at their own pace and convenience, making it an ideal platform for both beginners and experienced programmers seeking to enhance their skills.

Skills Up is an AI-powered platform designed to unlock your potential through personalized video-based learning. The app offers a wide range of topics, from coding languages like Python to design with CSS, curated YouTube playlists, interactive quizzes, and seamless video integration. With intelligent prompting powered by GPT-3, Skills Up understands your preferences and tailors your learning experience. Start your learning adventure today and discover, grow, and acquire new skills with ease.

AskCodi is an AI coding assistant that helps developers write code more efficiently. It provides real-time suggestions, code completion, and error detection to streamline the coding process. With its advanced algorithms, AskCodi can understand the context of the code and offer relevant recommendations. By leveraging machine learning techniques, AskCodi continuously learns and improves its suggestions to better assist developers in their coding tasks.

Stackademic is an AI-powered platform that offers free education to anyone interested in pursuing a career in Software Development. The platform aims to provide accessible learning resources to individuals worldwide, leveraging artificial intelligence to enhance the learning experience. Stackademic covers a wide range of topics related to software development, including city planning, personalized learning, big data in finance, essential software tools for landlords, and AI-powered video editing. With a focus on innovation and efficiency, Stackademic equips software developers with the tools and knowledge necessary to excel in their field.

AnyLearn.ai is an AI-powered platform that offers a wide range of courses and guides generated by artificial intelligence. It provides users with the opportunity to learn about various topics in a structured and comprehensive manner. The platform leverages the power of AI to create personalized learning experiences for individuals seeking to enhance their knowledge and skills.

The website is a platform that provides information and resources related to web content. Users can access various articles, guides, and tools to enhance their understanding of web development, design, and digital marketing. The platform aims to assist individuals in improving their online presence and skills through valuable content and practical insights.

Offthreadr is an AI-powered course platform designed to enhance the learning experience for users on the go. It offers a unique approach to course completion by enabling users to interact with course content, chat for clarification, and receive motivation from a supportive community. With Offthreadr, users can access short course snippets, get instant answers to their questions through AI, and enjoy offthreaded learning to boost their learning outcomes.

Bloom Home is an AI-powered platform that offers personalized learning plans to help users unlock their potential. The platform utilizes advanced AI technology to tailor learning plans according to individual needs and goals, ensuring accelerated growth through optimized content and pacing. With an intuitive user interface and user experience design, Bloom Home makes learning a seamless and enjoyable experience. Users can choose any topic they want to learn, from cryptography to music, and the AI customization feature analyzes responses to create personalized learning plans. Testimonials from users highlight the platform's effectiveness in helping them learn new skills. Join Bloom Home to transform your learning journey and join thousands of learners who have benefited from the platform.

Wilco is an AI-powered learning platform that offers personalized, immersive, and endless learning experiences for individuals, employees, customers, and candidates. It provides a comprehensive library of AI and technical training curriculum, adaptive learning technology, and a creator platform for generating hands-on labs. Wilco's AI engine tracks user progress and community data, offering a unique and engaging learning environment. The platform is trusted by leading products and offers quests in various programming languages, making learning fun and interactive.

Taiga is an AI-powered coding mentor that integrates with Slack. It provides real-time feedback, guidance, and tailored recommendations to help users learn software engineering in a fun and interactive way. Taiga offers a wide range of features, including step-by-step guidance, real-time answers, personalized learning experiences, seamless Slack integration, and accessibility on multiple devices.

DataCamp is an online learning platform that offers courses in data science, AI, and machine learning. The platform provides interactive exercises, short videos, and hands-on projects to help learners develop the skills they need to succeed in the field. DataCamp also offers a variety of resources for businesses, including team training, custom content development, and data science consulting.

Codiga is a static code analysis tool that helps developers write clean, safe, and secure code. It works in real-time in your IDE and CI/CD pipelines, and it can be customized to meet your specific needs. Codiga supports a wide range of languages and frameworks, and it integrates with popular tools like GitHub, GitLab, and Bitbucket.

BugFree.ai is an AI-powered platform designed to help users practice system design and behavior interviews, similar to Leetcode. The platform offers a range of features to assist users in preparing for technical interviews, including mock interviews, real-time feedback, and personalized study plans. With BugFree.ai, users can improve their problem-solving skills and gain confidence in tackling complex interview questions.

Roadmapped.ai is an AI-powered platform designed to help users learn various topics efficiently and quickly. By providing a structured roadmap generated in seconds, the platform eliminates the need to navigate through scattered online resources aimlessly. Users can input a topic they want to learn, and the AI will generate a personalized roadmap with curated resources. The platform also offers features like AI-powered YouTube search, saving roadmaps, priority support, and access to a private Discord community.

This repository is part of the Certified Cloud Native Applied Generative AI Engineer program, focusing on the fundamentals of Prompt Engineering, Docker, GitHub, and Modern Python Programming. It covers the basics of GenAI, Linux, Docker, VSCode, Devcontainer, and GitHub. The main emphasis is on mastering Modern Python with Typing, using ChatGPT as a Personal Python Coding Mentor. The course material includes tools installation, study materials, and projects related to Python development in Docker containers and GitHub usage.

This repository serves as an educational resource for pharmaceutical and chemistry students to learn the basics of Deep Learning through a collection of Jupyter Notebooks. The content covers various topics such as Introduction to Jupyter, Python, Cheminformatics & RDKit, Linear Regression, Data Science, Linear Algebra, Neural Networks, PyTorch, Convolutional Neural Networks, Transfer Learning, Recurrent Neural Networks, Autoencoders, Graph Neural Networks, and Summary. The notebooks aim to provide theoretical concepts to understand neural networks through code completion, but instructors are encouraged to supplement with their own lectures. The work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

AI Driven Dev Community is a repository aimed at helping developers become more efficient by utilizing AI tools in their daily coding tasks. It provides a collection of tools, prompts, snippets, and agents for developers to integrate AI into their workflow. The repository is regularly updated with new resources and focuses on best practices for using AI in development work. Users can find tools like Espanso, ChatGPT, GitHub Copilot, and VSCode recommended for enhancing their coding experience. Additionally, the repository offers guidance on customizing AI for developers, installing AI toolbox for software engineers, and contributing to the community through easy steps.

LearnOpenCV is a repository containing code for Computer Vision, Deep learning, and AI research articles shared on the blog LearnOpenCV.com. It serves as a resource for individuals looking to enhance their expertise in AI through various courses offered by OpenCV. The repository includes a wide range of topics such as image inpainting, instance segmentation, robotics, deep learning models, and more, providing practical implementations and code examples for readers to explore and learn from.

Start Machine Learning in 2024 is a comprehensive guide for beginners to advance in machine learning and artificial intelligence without any prior background. The guide covers various resources such as free online courses, articles, books, and practical tips to become an expert in the field. It emphasizes self-paced learning and provides recommendations for learning paths, including videos, podcasts, and online communities. The guide also includes information on building language models and applications, practicing through Kaggle competitions, and staying updated with the latest news and developments in AI. The goal is to empower individuals with the knowledge and resources to excel in machine learning and AI.

This repository is a compilation of excellent ML and DL tutorials created by various individuals and organizations. It covers a wide range of topics, including machine learning fundamentals, deep learning, computer vision, natural language processing, reinforcement learning, and more. The resources are organized into categories, making it easy to find the information you need. Whether you're a beginner or an experienced practitioner, you're sure to find something valuable in this repository.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

This repository serves as a comprehensive hub for updates on generative AI research, interview materials, notebooks, and more. It includes monthly best GenAI papers list, interview resources, free courses, and code repositories/notebooks for developing generative AI applications. The repository is regularly updated with the latest additions to keep users informed and engaged in the field of generative AI.

Awesome AI is a curated list of artificial intelligence resources including courses, tools, apps, and open-source projects. It covers a wide range of topics such as machine learning, deep learning, natural language processing, robotics, conversational interfaces, data science, and more. The repository serves as a comprehensive guide for individuals interested in exploring the field of artificial intelligence and its applications across various domains.

Pixeltable is a Python library designed for ML Engineers and Data Scientists to focus on exploration, modeling, and app development without the need to handle data plumbing. It provides a declarative interface for working with text, images, embeddings, and video, enabling users to store, transform, index, and iterate on data within a single table interface. Pixeltable is persistent, acting as a database unlike in-memory Python libraries such as Pandas. It offers features like data storage and versioning, combined data and model lineage, indexing, orchestration of multimodal workloads, incremental updates, and automatic production-ready code generation. The tool emphasizes transparency, reproducibility, cost-saving through incremental data changes, and seamless integration with existing Python code and libraries.

The 'bookmark-summary' repository reads bookmarks from 'bookmark-collection', extracts text content using Jina Reader, and then summarizes the text using LLM. The detailed implementation can be found in 'process_changes.py'. It needs to be used together with the Github Action in 'bookmark-collection'.

Torchtune is a PyTorch-native library for easily authoring, fine-tuning, and experimenting with LLMs. It provides native-PyTorch implementations of popular LLMs using composable and modular building blocks, easy-to-use and hackable training recipes for popular fine-tuning techniques, YAML configs for easily configuring training, evaluation, quantization, or inference recipes, and built-in support for many popular dataset formats and prompt templates to help you quickly get started with training.

Data-Juicer is a one-stop data processing system to make data higher-quality, juicier, and more digestible for LLMs. It is a systematic & reusable library of 80+ core OPs, 20+ reusable config recipes, and 20+ feature-rich dedicated toolkits, designed to function independently of specific LLM datasets and processing pipelines. Data-Juicer allows detailed data analyses with an automated report generation feature for a deeper understanding of your dataset. Coupled with multi-dimension automatic evaluation capabilities, it supports a timely feedback loop at multiple stages in the LLM development process. Data-Juicer offers tens of pre-built data processing recipes for pre-training, fine-tuning, en, zh, and more scenarios. It provides a speedy data processing pipeline requiring less memory and CPU usage, optimized for maximum productivity. Data-Juicer is flexible & extensible, accommodating most types of data formats and allowing flexible combinations of OPs. It is designed for simplicity, with comprehensive documentation, easy start guides and demo configs, and intuitive configuration with simple adding/removing OPs from existing configs.

Awesome LLM compression research papers and tools to accelerate LLM training and inference.

This repository serves as a comprehensive guide for technical teams interested in developing conversational AI solutions using Retrieval-Augmented Generation (RAG) techniques. It covers theoretical knowledge and practical code implementations, making it suitable for individuals with a basic technical background. The content includes information on large language models (LLMs), transformers, prompt engineering, embeddings, vector stores, and various other key concepts related to conversational AI. The repository also provides hands-on examples for two different use cases, along with implementation details and performance analysis.

日本語LLMの包括的な概要です。400ワード未満で、改行や引用符はありません。

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

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